https://brightquery.ai/

FAQs

Introduction to BrightQuery

BrightQuery was founded in 2019, building on academic research that began in 2006. Its founder, Jose M. Plehn, Ph.D., was an economics professor conducting research with U.S. federal statistical agencies to monitor the state of the economy. This work eventually evolved into a commercial effort, culminating in BQ’s creation.

Jose M. Plehn received the 2015 Notable Contribution to the Accounting Literature Award from the American Accounting Association for his impactful research.

Overview of BQ’s Data and Coverage

BrightQuery provides comprehensive U.S. company data for active and inactive businesses, covering:

  • Verified firmographics (name, EIN, IRS industry code)
  • Quarterly financials (revenue, net income, EBITDA, total assets)
  • Monthly employment and payroll data
  • Corporate family tree structures
  • Information on directors and officers
  • Business locations, loans, and stock authorizations
  • Credit scores, fraud detection, executive details, stock filings, and more

BQ tracks:

  • 100 million legal entities
  • 70 million businesses
  • 300 million addresses
  • 60 million business owners
  • 150 million employees

Most data spans back to 2010, with some elements available from 2017 onward. This diverse dataset supports research, due diligence, risk analysis, and economic insights.

Detailed information is available at:

Understanding Business Entities and Statuses

  • Private companies are privately owned and can be structured as LLCs, S-Corps, or C-Corps.
  • A legal entity is a registered business unit that may consist of one or multiple establishments.
  • An establishment is a business location, like a store or office, where a legal entity conducts operations.

A company or legal entity is marked inactive if it is dissolved, liquidated, or canceled according to state records. Establishments are also inactive if all related legal entities are inactive.

Changes in company counts or statuses occur due to:

  • Legal activity: Companies or entities become inactive if dissolved, liquidated, or canceled. Establishments follow the status of related legal entities.
  • Clustering: The clustering of legal entities into corporate family structures based on new filings can clarify their independence or interdependence.
  • Survivorship bias: Active indicators reflect currently operational businesses, meaning historical views may not include inactive companies.

These processes ensure that BQ provides a dynamic and accurate representation of the business ecosystem.

Updates, Historical Data, and Accuracy

BQ’s historical data spans from 2010 to the present and is updated monthly for employment and payroll data and quarterly for most financial metrics. Key features include:

  • Point-in-time data: Each dataset is rebuilt monthly to capture any amendments, preserving accurate historical records.
  • Benefits and comprehensive company data: Updated annually.

These frequent updates ensure the most accurate and up-to-date information is available to clients.

BQ’s financial data evolves due to:

  • Amendments: Companies revise data for up to seven years based on regulatory changes.
  • Corporate restructuring: Adjustments to corporate family structures impact reported financials.
  • Data revisions: Updates occur as new filings or amendments are received.

This ongoing refinement ensures the financial insights provided by BQ are current and accurate.

Data gaps or revisions happen due to:

  • Filing delays: Missing financials often result from gaps in publicly available filings, which BQ can address upon request.
  • State reporting: Monthly employment figures are occasionally delayed and revised when states provide updates. BQ uses imputation methods similar to the Census Bureau to ensure accuracy.

These updates maintain the reliability and completeness of BQ’s datasets.

BQ retains point-in-time historical data and amendments from public filings, ensuring a comprehensive and unbiased economic history.

BQ sources data from over 100,000 government offices and public sources, adhering to strict data acquisition policies:

  • No restricted sources: BQ avoids scraping or collecting data from restricted websites requiring login or CAPTCHA.
  • Privacy safeguards: Confidence scores assess data reliability, and no personally identifiable information (PII) is collected.

This robust sourcing and validation process ensures the accuracy and integrity of BQ’s data.

Technical and Operational Details

BQ uses Amazon S3 for secure data storage, with daily backups and additional native AWS backup support.

BQ data can be delivered as CSV files to an S3 bucket, and an API is also available for data access.

Specialized Data Details

BQ’s employee count includes U.S.-based W2 employees only. It excludes 1099 contractors and international workers.

Employment adjustments typically occur at year-end, causing a discontinuity between December and January data. This “true-up” process is standard and reflects official filings.

BQ’s financial data is derived primarily from taxes and company filings. Larger companies often have more complex structures, leading to potential discrepancies in financial reporting.

Privacy and Compliance

BQ does NOT have any PII including SSN, Passport Number, Driver’s license number etc.

BQ does not access confidential tax returns or personal information such as Social Security numbers or dates of birth. Tax-related financial data is derived from public filings.

Data Sources and Collection

BQ collects data from over 100,000 government offices and agencies, including:

  • Federal, state, and local departments
  • IRS, Department of Labor, Small Business Administration, U.S. Postal Service, SEC, and Secretaries of State
  • Industry-specific regulators in transportation, health, finance, and more
    Details are available here.

BQ collects supplementary data from:

  • Corporate websites
  • News articles and press releases
  • LinkedIn, Yelp, Google Maps, Better Business Bureau

These sources enhance company profiles by adding details such as LinkedIn URLs and address validations.

While the Economic Census is conducted every five years, BQ collects similar data monthly. BQ’s data is more extensive, covering financials, ownership, contacts, and more, supplementing gaps in government records caused by incomplete or erroneous survey responses.

Applications of BQ Data

Yes, BQ’s public record data can be utilized for purposes like credit assessment, sales, and marketing.

BQ has secured contracts through America’s Datahub Consortium (ADC) to:

  • Develop a National Secure Data Service (NSDS) for querying federal statistical data.
  • Build platforms for state and local government data queries, including unemployment, tax, DMV, and health records.
  • Establish AI-ready standards for federal statistical data.

BQ’s collaboration with the U.S. Census Bureau and other agencies enhances statistical products by filling gaps in survey data.